Back to all projects
AI/ML2025
Insurance RAG
RAG-based insurance document Q&A system
PythonRAGLLMVector Database
Problem
Insurance documents are complex and lengthy. Agents and customers struggle to find specific information about coverage, claims, and policy details.
Approach
Built a RAG pipeline for insurance documents with vector embeddings and LLM-powered Q&A. Document chunking, embedding generation, and semantic search for accurate retrieval with source citations.
Result
RAG pipeline with vector embeddings and LLM-powered Q&A for insurance policies with source citations.